Checkpoint 1: EDA

By Arturo, Payson, and Victoria

Does healthcare access affect the number of preventable hospital stays of certain racial groups at the county level?

Why this matters:

• Reduce preventable hospitalizations
• Equitable resource allocation
• Focus efforts where help is needed most

Data Overview

Source: County Health Rankings 2025

• “Ranks every county in each state on their Health Outcomes and Health Factors”

Clinical Care

• Preventable Hospital Stays (outpatient setting)
  • Providers (Primary Care, Physicans, Mental Health, Dentist)
  • Mammography Screening
  • Uninsured (Adults, Children)

Preventable Hospitalizations by County

Regression Analysis of Racial Disparities in Preventable Hospital Stays

Planned Approach:

• Outcome: Preventable hospital stays
• Predictors: Uninsured rate, provider ratio, race group

Modeling Strategy:

• Explore variable selection and regularization

Moving into modeling and interpretation

Completed:

• Defined research question
• Cleaned and preprocessed dataset
• Created initial EDA visualizations

Next Steps:

• Fit regression models
• Interpret disparities and validate model
• Create visual summaries and poster